README

Prime Agent: A Self-Improving RLM Harness



  Documentation •
  Verifiers •
  PRIME-RL



  
    
  
  
    
  



  
    
  


Prime Agent is an open-source coding and research agent for general and long-running work. It is designed around two core abstractions:

- The Recursive Language Model (RLM) treats context as variables (prompt-as-a-variable) and tools like recursive subagents as function calls (programmatic tool /sub-agent calling) inside a persistent REPL.
- The Continual Harness stores supplemental prompts, memories, skill descriptions, and reusable subagent specifications as durable state that Prime Agent can refine through small, evidence-backed updates, local to the session by default.

 Install

Install the latest stable version with the one-command installer:

bash
curl -fsSL https://app.primeintellect.ai/prime-agent/install.sh | sh


On Windows, install from PowerShell:

powershell
irm https://app.primeintellect.ai/prime-agent/install.ps1 | iex


The Windows installer downloads the latest stable Windows x64 build and verifies its checksum before installation.

 Why Prime Agent

Prime Agent combines a persistent Python control environment with durable harness state, so useful working context and reusable operating patterns can outlive a single chat window.

- Everything is programmatic: a persistent Python REPL is the built-in model tool; file operations, shell commands, tool use, subagents, and context management happen through code.
- Subagents are built in: rlm.spawn(...) spawns real child agents for parallel or background work and returns their results programmatically.
- The harness can improve: /refine reviews the current trajectory and can apply small, evidence-backed updates to supplemental harness state. It never rewrites the immutable base system prompt, and recorded snapshots support rollback.
- Skills are executable: skills are importable Python packages, and the built-in skill creator can turn recurring workflows into project or personal skills.
- Sessions run in the background: daemon-backed agents keep running when the terminal disconnects and can be reattached later.
- Agents communicate directly: running agents can exchange messages and orchestrate one another without routing everything through the user.
- Long tasks keep moving: automatic compaction, persistent goals, heartbeats, schedules, autonomous mode, and retained subagents preserve progress across turns and terminal sessions.

 Slack

Connect Slack from /mcp or run /mcp login slack inside Prime Agent to search
your workspace and use Slack tools. See the Slack connector guide
for OAuth setup and troubleshooting.

 Google Drive and Google Sheets

Connect Google's official Drive and Sheets MCP servers with your own Google
OAuth client: add them to mcpServers with clientId, clientSecret,
callbackPort, and scopes, then run /mcp login . See the
Google Drive and Google Sheets guide for the
Google Cloud setup and the tool mapping.

 Clipboard over SSH a